Review: the predictability of the extra-tropical stratosphere on monthly timescales and its impact on the skill of tropospheric forecasts

Extreme variability of the winter- and spring-time stratospheric polar vortex has been shown to affect extratropical tropospheric weather. Therefore, reducing stratospheric forecast error may be one way to improve the skill of tropospheric weather forecasts. In this review, the basis for this idea is examined. A range of studies of different stratospheric extreme vortex events shows that they can be skilfully forecasted beyond five days and into the sub-seasonal range (0-30 days) in some cases. Separate studies show that typical errors in forecasting a stratospheric extreme vortex event can alter tropospheric forecasts skill by 5-7% in the extratropics on sub-seasonal timescales. Thus understanding what limits stratospheric predictability is of significant interest to operational forecasting centres. Both limitations in forecasting tropospheric planetary waves and stratospheric model biases have been shown to be important in this context.

A survey of simultaneous observations of the high-latitude ionosphere and interplanetary magnetic field with EISCAT and AMPTE-UKS

This paper surveys the results of simultaneous observations by the EISCAT incoherent scatter radar and the AMPTE-UKS satellite, made during three periods in September and October 1984, when AMPTE-UKS was in the solar wind on the dayside of the Earth and the UK-POLAR EISCAT experiment was measuring ionospheric parameters at invariant latitudes 70.8–75.0°. A total of 42 h of EISCAT convection velocity data, with 2.5 min resolution, were obtained, together with 28 h of simultaneous 5 s resolution AMPTE-UKS observations of the solar wind and interplanetary magnetic field (IMF). The general features of the AMPTE-UKS data are described in Section 2 and those of the EISCAT data are described in Sections 3 and 4. The main subjects discussed are the form of the plasma convection patterns and their dependence on all three components of the IMF (Section 5), the ionospheric response to abrupt changes in the IMF (Section 6), in particular a sharp ‘southward turning’ of the IMF on 27 October 1984, and a crossing of an IMF sector boundary. Section 7 describes ‘short lived rapid flow burst’, which are believed to be related to flux transfer events at the magnetopause.

Creating and implementing a biodiversity recording app for teaching and research in environmental studies

This case study reports on the development of a bespoke mobile recording app for collating records of biodiversity sightings on a University campus. This innovative project was achieved through a multi-disciplinary partnership of staff and students. It is hoped that the app itself will benefit lecturers by streamlining data collection during teaching and learning activities, whilst engaging students and highlighting the wealth of diversity available on campus

Mapping power law distributions in digital health social networks: methods, interpretations, and practical implications

BACKGROUND: Social networks are common in digital health. A new stream of research is beginning to investigate the mechanisms of digital health social networks (DHSNs), how they are structured, how they function, and how their growth can be nurtured and managed. DHSNs increase in value when additional content is added, and the structure of networks may resemble the characteristics of power laws. Power laws are contrary to traditional Gaussian averages in that they demonstrate correlated phenomena. OBJECTIVES: The objective of this study is to investigate whether the distribution frequency in four DHSNs can be characterized as following a power law. A second objective is to describe the method used to determine the comparison. METHODS: Data from four DHSNs—Alcohol Help Center (AHC), Depression Center (DC), Panic Center (PC), and Stop Smoking Center (SSC)—were compared to power law distributions. To assist future researchers and managers, the 5-step methodology used to analyze and compare datasets is described. RESULTS: All four DHSNs were found to have right-skewed distributions, indicating the data were not normally distributed. When power trend lines were added to each frequency distribution, R(2) values indicated that, to a very high degree, the variance in post frequencies can be explained by actor rank (AHC .962, DC .975, PC .969, SSC .95). Spearman correlations provided further indication of the strength and statistical significance of the relationship (AHC .987. DC .967, PC .983, SSC .993, P<.001). CONCLUSIONS: This is the first study to investigate power distributions across multiple DHSNs, each addressing a unique condition. Results indicate that despite vast differences in theme, content, and length of existence, DHSNs follow properties of power laws. The structure of DHSNs is important as it gives insight to researchers and managers into the nature and mechanisms of network functionality. The 5-step process undertaken to compare actor contribution patterns can be replicated in networks that are managed by other organizations, and we conjecture that patterns observed in this study could be found in other DHSNs. Future research should analyze network growth over time and examine the characteristics and survival rates of superusers.